Tuesday, May 24, 2016

CSF: The Most Important Metric You've Never Used

Don Sexton

Don Sexton is Professor of Marketing and of Decisions, Risk, and Operations at Columbia University. He’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.

As a preview to his presentation “CSF: The Most Important Metric You’ve Never Used,” Don shares insights on the importance of CSF for business success.

Peggy L. Bieniek, ABC: Why is CSF the most important metric for the success of your business?
Don Sexton: CSF (Customer Surplus Factor) is the ratio of a customer’s willingness to pay to the price being charged. The higher that ratio, the more likely the customer is to make the purchase.

CSF therefore summarizes most other marketing metrics such as awareness, knowledge, preference – even likelihood to recommend – and so is a very efficient approach to understanding a company’s position in the marketplace.

In many cases, we have found that CSF results in highly accurate predictions of financial outcomes such as revenue and contribution.

In addition, CSF is a metric that leads to actions. Willingness to pay can be managed with many marketing tools. CSF can indicate which marketing actions will lead to the most attractive financial results.

PB: What are the key differences between CSF and KPI?
DS: A KPI is a Key Performance Indicator. Managers use KPIs to monitor their ongoing business situation. KPIs should consist of both lagging indicators (which show where you've been) and leading indicators (which show where you're heading). 

CSF is a very powerful leading indicator of what financial outcomes you can expect given your strategy. CSF should most certainly be included among the KPIs that a marketing manager regularly reviews.

PB: How is CSF typically used?
DS: CSF is used to provide insights for strategy in both short-run and long-run competitive situations. Traditional techniques such as marketing mix modeling primarily focus on resource allocation over the next year. 

CSF enables managers to not only plan for the short run, but also for the long run. CSF allows managers to understand the position of their product and service in the customer’s mind and suggests what must be done over time to improve their competitive position.

PB: How should CSF be used for successful business outcomes?
DS: CSF should be monitored frequently – quarterly or semi-annually – to provide managers with steering control, the ability to set clear objectives and to forecast results of marketing actions before they are implemented.

PB: What will people gain from attending your conference presentation?
DS: Managers attending this session will understand an innovative way to analyze their competitive situation, an approach well-grounded in marketing and economics and proven to work by several companies, which clearly links marketing actions to financial outcomes and which is relatively easy to put into practice.

Want to hear more from Don? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.

Brilliance@Work profile originally published on www.starrybluebrilliance.com


Peggy L. Bieniek, ABC is an Accredited Business Communicator specializing in corporate communication best practices. 

Connect with Peggy on LinkedInTwitterGoogle+, and on her website at www.starrybluebrilliance.com. 





Monday, May 23, 2016

How to Understand the Next Generations and their Trends for Guaranteed Reach

Jane Buckingham

Jane Buckingham is Founder and CEO, Trendera, and a best-selling author. She’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.
As a preview to her presentation “Deciphering Generations X, Y, and V: How to Understand Next Generations and their Trends for Guaranteed Reach,” Jane shares insights on the importance of understanding generations for business success.

Peggy L. Bieniek, ABC: What are some key strategies for marketing to different generations?
Jane Buckingham: There are a few ways to approach this. If your brand is going for a particular age and niche, then you want a generational approach, in which case you want to appeal to the emotional and psychographic needs of that particular generation. Try to understand what sets them apart from the previous generations.

Is it a tone, is it a location, is it inspiring the brand fanatics and hypertailoring (appealing to younger generations), or redefining happiness and success (more Gen X), or helping to inspire and enlighten (for Gen Y)?

On the other side, if you are looking to cut across generations, you may be looking to talk to a mindset over the market. Looking to understand what your particular group of people thinks, what is it about your brand that will be appealing to someone no matter what their age? Are they fitness enthusiasts looking for purpose? Are they looking for comfort? Are they looking for safety? Some of these core values are cross generational and may be appealing no matter what the age.

PB: How do you address the challenge of everyone agreeing on a standard of when generations begin and end?
JB: This has gotten a lot trickier since Douglas Coupland wrote Generation X in 1991, and we started segmenting generations by 15 year periods versus 20 year periods. It became much less clear where and when a generation starts and stops.

Technically, generations are really defined by the factors that affect them as they grow up, and the cultural shifts in the world. But, how something will affect someone who is two at the time a generation is coined is going to be much different than how it affects someone who is 18 at the time it is coined, so usually someone who is right in the middle feels most 'like' that generation.

So, even if people are off by a year or two, it doesn't really matter. The bigger challenge is that often marketers are talking about a marketing segment by a "media" age that can be purchased (like 18-34 or 35-54), and that will cut across two generations, but they don't want to really think about that so they just sort of move the dates to accommodate the media buy.

They will say Millennials are 18-34, when really right now 18-34 would include Millennials and Gen V. In fact, many people seem to think that Millennials are still teenagers because they've been the emerging generation for so long, when actually the youngest of them are about 20.

PB: How is data the greatest equalizer in marketing?
JB: Data helps to try to "prove" things. The idea is that big data can help quantify what we speculate about and provide greater insight into what we are thinking, doing and how we are behaving.

I LOVE data. And I love that we now have more access to more data than ever. It allows retailers to see how consumers shop, and how price and value works versus brand.

One of the most exciting things about data for marketers and consumers is that advertising is going to start feeling less and less like advertising. 

Thanks to increasingly sophisticated analytics and predictive modeling, both big and small brands can tap information that will allow them to connect consumers to products and services that are truly relevant and interesting to them.

That said, data isn't a silver bullet, and can't and shouldn't be seen as one. Numbers only tell you part of the story and you need to interpret them carefully. It's just as important to talk to your consumer to understand the why behind the numbers and any subtleties that the numbers might not reveal.

PB: What will people gain from attending your conference presentation?
JB: I'm hoping that attendees will better understand the differences between the generations - as marketers, employers, parents, siblings - so that they can better relate to them, market to them and listen to them.

In addition, I'll be talking about the macro trends that will be affecting these generations for the next several years as well as some fun trends that are happening now.

Overall, I want the audience to feel like they are better versed in who their next consumers are and who they will be.

Want to hear more from Jane? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.


Brilliance@Work profile originally published on www.starrybluebrilliance.com


Peggy L. Bieniek, ABC is an Accredited Business Communicator specializing in corporate communication best practices. 


Connect with Peggy on LinkedInTwitterGoogle+, and on her website at www.starrybluebrilliance.com. 





Thursday, May 19, 2016

How can I blend sample sources without impacting my data?

By: Susan Frede, Vice President of Research Methods and Best Practices, Lightspeed GMI

Research has consistently shown that all panels are not the same. Recruitment sources and management practices vary, and this can cause differences among panels. Beyond panels, there are other sources of online survey respondents, such as river, dynamic, and social media sources – and these can produce data that is different from each other, as well as different from panels. Given the wide variety of sample sources, and their benefits and drawbacks in cost and quality, researchers often struggle with the question, “How can I blend in other sources without impacting my data?”

To help our clients answer this question, Lightspeed GMI modeled the impact of adding in a second source of online respondents. For this exercise we are considering two sources – Source A and Source B. The assumption is that Source A is the primary source and there is a need to blend in Source B. There are differences in the scores between the two sources for the concept measures. For example, the purchase intent scores are higher for Source B:


Given the differences, adding in Source B has the potential to impact the scores. However, it takes a large influx of Source B to impact results (see Chart 1 – Impact on Purchase Intent Scores). The proportion of respondents saying they definitely would buy goes from 7.8% to 8.6% when the sample blend is 50% Source A and 50% Source B. The percentage saying they probably would buy goes from 16.6% to 19.0%. Neither change is statistically significant with a typical base of 400 respondents and a 95% confidence level. 


Another way to look at the impact is to examine the number of differences on scores in the blended sample compared to 100% of Source A (see Chart 2 – Number of Differences versus 100% Source A). By adjusting the proportion of sample coming from each source, it is possible to identify the point at which concept scores are impacted. Five key concept measures have been evaluated (purchase intent, uniqueness, liking, relevancy, and likelihood to recommend). For example, when 75% of the sample is from Source A and 25% from Source B, only one difference of +/-2% is observed versus a 100% Source A sample. Even when the sample is adjusted to a 55/45 blend all the differences are less than or equal to +/-3, which in most cases is not statistically significant. 


The data suggests that as long as additional sources account for 40% or less of the total sample, data should not be impacted. 

However, Lightspeed GMI recommends a more conservative cap of 25-30%. Because there are several situations that may call for an even more conservative blend, consider the following before making any changes:
  1. Tracker and wave studies – Trendability is key in tracker and wave studies. Rather than making one big change it is better to make a series of small changes (+/-10%) from week to week or wave to wave and monitor the impact. 
  2. Unproven panel and dynamic sources – Until the quality of an unproven source is understood it is better to be conservative in the amount blended in.
  3. Low incidence studies – We have seen a higher proportion of questionable behavior on low incidence studies, so it is important to be more conservative when making changes.

This analysis also shows that we don’t have to maintain an exact source blend for trackers (e.g., 50% Source X and 50% Source Y), which allows us to more efficiently use sample. As long as we are within +/-5 to 10% for each source (e.g., 40-60% Source X), data will not be impacted.





Wednesday, May 18, 2016

Does the Data Answer Your Business Questions?


Camille P. Schuster, Ph.D.

Camille P. Schuster, Ph.D. is Professor, Marketing, for the College of Business Administration at California State University San Marcos and President of Global Collaborations Inc. She’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.

As a preview to her presentation “Playing Detective with Data,” Camille shares insights on how the questions you ask while analyzing the data are critical for successful business outcomes.

Peggy L. Bieniek, ABC: How should organizations innovate and improve the way they use data in their business operations?
Camille P. Schuster, Ph.D.: 
 All organizations have a tremendous amount of data available to them including consumer information, heavy users vs. light users, average purchase size vs. large purchase, number of purchases per week or month or quarter, feedback forms, on time payment data, social media data, contact information, and more.

How to use it depends upon the business question. Analyzing data for the sake of analyzing is not particularly helpful. Start with the business question, analyze the data you have, determine whether it is cost effective to obtain other data you would like to have, and move forward.

PB: What is the role of data in data analysis?
CS: Data is the raw material that can be used to solve problems. The data itself includes numbers or words (if analyzing text) to be transformed into a standard format for comparison and manipulation purposes. When the comparisons and manipulations are complete, then you have information.

The most valuable skill of all is the ability to interpret what the information means and how it can be used to solve a problem. All three steps are critical for success and require different skill sets.

Preparing and cleaning the data to make it usable for use in specific software requires one set of skills. Knowing which tools are needed to perform what calculations requires a different set of skills. Being able to understand the data and what calculations were formed to be able to interpret the results and make recommendations to solve business problems requires another set of skills. Understanding each of the steps and the interaction between the steps is essential.

PB: What are the attributes of a successful system for reliable data analysis?
CS: The attributes of a successful system include:
- Knowing the questions that need to be answered
- Determining whether you have data that can answer those questions or can get that data
- Having people with the skills to perform the necessary steps
- Having the appropriate hardware and software for the analyses you need to do

PB: What will people gain from attending your conference presentation?
CS: My presentation will demonstrate how the questions you ask influence your results and understanding of the situation which, in turn, will change your business recommendations.

Want to hear more from Camille? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.

Brilliance@Work profile originally published on www.starrybluebrilliance.com



Peggy L. Bieniek, ABC is an Accredited Business Communicator specializing in corporate communication best practices. 

Connect with Peggy on LinkedInTwitterGoogle+, and on her website at www.starrybluebrilliance.com. 





Tuesday, May 17, 2016

How Research Teams Can Stay Relevant in the Digital Age

“Embrace consumers in a transparent fashion. The people are the heroes now”



Is your research operations team ready for the new face of consumer insights? Today, it’s key for research teams to remain relevant in the midst of changing digital age and be able to create a roadmap to success to stay relevant.

That’s why we sat down with Robert Moran, Partner, Brunswick Group Global Head of Insight, who knows this well and offers fellow industry professional some advice on the subject.

How are research operations teams changing in the digital age?

Moran: Many aren’t and that’s a problem for them and their organizations.  The short answer is that they need to invest heavily in social media and traditional media listening skills, become much faster and more agile and act as futurists – anticipating trends based on a wide array of inputs.

What is your advice to traditional researchers trying to stay relevant in the fast changing market research and consumer insights space?

Moran: Strengthen your synthesis skills, drawing insights from a number of data streams.  
Focus on speed and time to insight. The political polling community may be a source of inspiration here.
Work to dramatically improve your communications to management. Most market research is poorly communicated.

What is the best way to build a high performance team in today’s MRX world?

Moran: Hire for curiosity, energy and communications ability. The field has traditionally over-focused on hiring for managers of the research process. That was rational when the objective was gathering data, but is less helpful when data is ubiquitous.

Why is it important to be an agile market research today?

Moran: A significant portion of market research is locked up in brand trackers that cost too much to answer basic, 20th century questions about the business. Budgets need to be dramatically reworked to answer critical, in-the-moment questions that management has at the strategic level.

How can a company create a research innovation culture?


Want to hear more from Robert? Hear his presentation “An Insider Look: Deconstructing the Current Paradigms” at TMRE in Focus: The New Face of Consumer Insights later this month.

From the producers of TMRE: The Market Research Event, The New Face of Consumer Insights explores how companies are redefining their structures, processes, skillsets and team composition to ensure future relevance in this fast changing environment. To learn more about the conference and to register, click here: http://bit.ly/1NwN299





Monday, May 16, 2016

Insights to Reach Shoppers Where they Plan, Shop & Share at OmniShopper

What does the physical store environment have in common with a digital shopping cart and a mobile phone?

Even just five years ago it may have been difficult to bring the pieces together, but in today's retail landscape, it's easier to connect the dots. It's a connected consumer.

You know that the retail industry has been undergoing a major transformation. But what are you doing to adapt and keep up with the changes? Let OmniShopper 2016 be your partner for success.
OmniShopper has a reputation for attracting the most elite and sharp-minded retailers in the industry. 

The 2016 event is no exception. We're uniting retailers with their brand partners to, collaboratively define the new retailer/manufacturer partnership and address total store shopability to create successful omnichannel experiences now and in the future.

Featured sessions include:

·         Jet.com, Lowe's Home Improvement, Unliever, PepsiCo and ConAgra discuss The State of the Industry: The Future of Retail, including technologies driving retail innovations, complete shopper control, how the rise of eCommerce/omnichannel mentality has impacted traditional retail sales and much more.
·         Mall of America reveals how they used emerging technologies like robotics, virtual reality, social media and mobile to Innovate the Physical Retail Space.
·         Wrigley explores how to Collaborate to Drive Impulse in an Evolving Retailer Landscape. 
·         The Hershey Company, Bayer and Campbell Soup share how to Reach Shoppers Where They Plan, Shop and Share.
Plus, INDUSTRY LEGEND Daniel Kahneman, Nobel Prize Winner in Economic Sciences and Best-Selling Author, Thinking, Fast and Slow will take the keynote stage: A Conversation with Daniel Kahneman to Understand What Shapes Our Choices, Judgements and Decisions.

As humans, we think we make rational decisions, but the truth is we are subject to many biases that affect our decision making. Daniel Kahneman explains the two systems that drive our thinking. Everything from personal happiness, playing the stock market, making purchasing decisions, and planning a vacation can be understood by knowing how these systems shape our judgements and decisions. Should we trust our intuitions?  

Have a question you want Daniel to answer? Tweet it using hashtag #OmniAsksDaniel and we'll add it to the schedule!

Download the 2016 agenda: http://bit.ly/1XfAlkG

Use code OMNI16BL for $100 off the current rate. Buy tickets here: http://bit.ly/1XfAlkG

The future of retail won't be defined in isolation. Make your voice heard at OmniShopper this July.

Cheers, 
The OmniShopper Team
@OmniShopper
#OmniShopperConf






Friday, May 13, 2016

Customer Service Matters More than You Think


Wayne Huang

Wayne Huang is a Research Manager at Twitter. He’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.

As a preview to his presentation “Mo’ Problems, Mo’ Money: Customer Service Matters More than You Think,” Wayne shared insights on how social media is transforming the way consumers interact with brands.


Peggy L. Bieniek, ABC: How does Twitter help to shape the future of online social media?
Wayne Huang:  As someone with a background in both engineering and in social science, what I find most interesting about Twitter is how it has completely upended the way we communicate.

We’re used to jumping through hoops to talk to a human being at a company. It’s nearly impossible these days to find the phone number of the company you’re trying to reach. But, what strikes me most about Twitter is that brands actually proactively engage in conversations with customers, and not hide behind a maze of automated phone menus.

One of my most memorable Twitter experiences was when I once tweeted a question to Virgin Atlantic, and they responded to my tweet in less than three seconds. That was an incredible interaction that I’ll always remember. It’s a leveling of the playing field between big companies and consumers that wouldn’t have happened without social media.

PB: How does Twitter data help tell a marketing story?
WH: Twitter is an incredibly rich source of data. Every day, close to half a billion tweets are sent. Search for any topic, and I guarantee you’ll find someone tweeting about it.

For brands, Twitter is like the biggest permanent focus group in the world, free for you to search to find what your customers really think about you. For example, John Legere, the CEO of T-Mobile, famously spends a ton of time on Twitter searching for what his customers love and hate about T-Mobile. He also responds directly to tweets from users, who were so shocked that he tweeted them that they’re now clamoring to switch to T-Mobile.

PB: How can brands do better on Twitter?
WH: Companies should see Twitter as the public, human face of their brands. By human, I mean imagine that your brand is a human being, and imagine your social media conversations as real human conversations you’re having with other human beings.

For example, no one in real life actually wants to be friends with someone who just keeps blabbing on about how he or she is the greatest person in the world. Similarly, your Twitter profile shouldn’t be a one-way conversation where you just post links to corporate press releases or generic product shots.

Instead, engage with your customers. Post advice and tips. Answer their questions and respond to their tweets as quickly as possible. Retweet your users’ content, such as when they post a beautiful photo. Like your users’ content, and thank them when they give you feedback. That gives your users the feeling of a “win.”

It’s basic social reciprocity— just as we need to give and take in our daily relationships, so should brands on Twitter.

PB: What will people gain from attending your conference presentation?
WH: Businesses often struggle to understand what their customers are really thinking. In my presentation, I’ll talk about the pitfalls of relying on self-reported surveys when conducting customer research.

I’ll then showcase a novel experiment we ran on Twitter where we tested how a good (or bad) customer service experience from a brand affects the customer’s future decision-making process.

In that experiment, we found thousands of users who had a customer service interaction with an airline on Twitter and how we quantified— in dollar terms— how the customer changed their behavior after those positive interactions. For example, after a good experience, is that customer more willing to fly the airline again? Or will they just default for the cheapest carrier?

We’ll also discuss some interesting findings from recent psychology experiments that businesses should adopt if they want to impress their customers.

Want to hear more from Wayne? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.

Brilliance@Work profile originally published on www.starrybluebrilliance.com



Peggy L. Bieniek, ABC is an Accredited Business Communicator specializing in corporate communication best practices. 

Connect with Peggy on LinkedInTwitterGoogle+, and on her website at www.starrybluebrilliance.com. 





Thursday, May 12, 2016

Danfeng Li Shares Insights on Alibaba's Strategy in the Mobile Marketplace

Danfeng Li

Danfeng (Dan) Li is a Director at the Alibaba Group, where he oversees the web/mobile analytics team that provides business intelligence and predictive analysis solutions for web pages, mobile apps and smart devices. 

He’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.
As a preview to his presentation “Get More Whales out of Your Mobile Game Players,” Dan shared some insights on Alibaba’s strategy in the mobile marketplace.

Peggy L. Bieniek, ABC: How did Alibaba help grow the global online and mobile marketplace?
Dan Li: In 2003, Alibaba created the Taobao platform to help micro and small businesses sell their products online for free. For the first five years, Taobao did not generate any revenue and did not become profitable until 2010. During this time frame, it grew from 0 to more than 95% of the Chinese online marketplace.

We truly believe that we can only benefit by helping small businesses. We were very patient and applied strategies that are applicable to China businesses, like a customer care system called WangWang, and Alipay to address trust and credit challenges. Of course, Alipay became a very successful story in itself.

A couple of years ago, we noticed the trend that people were moving from shopping online to shopping on mobile. We established many strategies to encourage people shopping on mobile. Mobile sales quickly surpassed online sales. We were just a small step ahead of our customers and our competitors.

Now being the largest marketplace online and on mobile, we continue our innovation with the help of our 10 million merchants and billions of consumers through personalization, streamlining logistics, and experimenting with a C2B business model.

PB: What are key strategies for successful mobile game monetization?
DL: The key is to find the potential "whale" players who are willing to pay for your game. We built machine learning models to help identify those players. We target our sales and marketing efforts to them. The key for us to do this successfully is we know a lot about new customers through monitoring user behavior across games and apps.

PB: How will mobile game monetization change in the future?
DL: I can only speak for the Chinese market. Right now, venture capital (VC ) money is not that easy to get, so monetization becomes more and more important in the near future. Also, in the Chinese market, the game industry is still very simple. We need a more data-driven approach to make the process more efficient.

PB: What will people gain from attending your presentation at the conference?
DL: I'll share some of our efforts to help the game industry in China and some statistics and trends in the Chinese mobile gaming industry.

Want to hear more from Dan? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.

Brilliance@Work profile originally published on www.starrybluebrilliance.com



Peggy L. Bieniek, ABC is an Accredited Business Communicator specializing in corporate communication best practices. 

Connect with Peggy on LinkedInTwitterGoogle+, and on her website at www.starrybluebrilliance.com.